Probabilistic Robust Path Planning for Nonholonomic Arbitrary-Shaped Mobile Robots Using a Hybrid A* Algorithm

To guarantee safe motion planning, the underlying path planning algorithm must consider uncertainties and uncertain state information related to static, dynamic obstacles. This paper proposes novel hybrid A* (HA*) algorithms that uncertainty in of a mobile robot, position static obstacles, velocity Variants HA* are proposed wherein soft constraint is used cost function instead chance constraints for probability guarantees. The offers tradeoff between traveling distance safety paths without pruning additional nodes. Furthermore, this introduces method considering shape robot probabilistic planning. compared with existing performance evaluated using Monte Carlo simulation. Compared robust algorithms, significantly improved excessively increasing travel computational time. results also showed obstacles were safely avoided, which contrast conventional has high collision. In addition, approach led safer overall.